Evidence map›Paper›PMID 38624976›Full record

ReviewSystems microbiology and biomanufacturing2022

Bioreactor control systems in the biopharmaceutical industry: a critical perspective.

Sagnik Mitra, Ganti S Murthy

Abstract readReview
In one paragraph

Review in Systems microbiology and biomanufacturing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Review
  2. Article
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  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Compression bioreactor for cultured meat.Current research in food science · 2026
    Article
  11. Article
  12. Article
  13. Embedded IoT Design for Bioreactor Sensor Integration.Sensors (Basel, Switzerland) · 2024
    Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Review
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sagnik MitraDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Indore, 453552 India.
Ganti S MurthyDepartment of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Indore, 453552 India.ORCID 0000-0003-2774-9559

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industrial-scale bioprocessing underpins much of the production of pharmaceuticals, nutraceuticals, food, and beverage processing industries of the modern world. The profitability of these processes increasingly leverages the economies of scale and scope that are critically dependent on the product yields, titers, and productivity. Most of the processes are controlled using classical control approaches and represent over 90% of the industrial controls used in bioprocessing industries. However, with the advances in the production processes, especially in the biopharmaceutical and nutraceutical industries, monitoring and control of bioprocesses such as fermentations with GMO organisms, and downstream processing has become increasingly complex and the inadequacies of the classical and some of the modern control systems techniques is becoming apparent. Therefore, with increasing research complexity, nonlinearity, and digitization in process, there has been a critical need for advanced process control that is more effective, and easier process intensification and product yield (both by quality and quantity) can be achieved. In this review, industrial aspects of a process and automation along with various commercial control strategies have been extensively discussed to give an insight into the future prospects of industrial development and possible new strategies for process control and automation with a special focus on the biopharmaceutical industry. Supplementary Information: The online version contains supplementary material available at 10.1007/s43393-021-00048-6.

Indexed as

Advanced process controlBiopharmaceuticalsBioreactor control systemsDigitizationIndustrial automationSingle-use technology

Identifiers

PMID38624976
PMCPMC8340809

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.